您好,登錄后才能下訂單哦!
本文研究的主要是python處理csv數據動態顯示曲線,分享了實現代碼,具體如下。
代碼:
# -*- coding: utf-8 -*- """ Spyder Editor This temporary script file is located here: C:\Users\user\.spyder2\.temp.py """ """ Show how to modify the coordinate formatter to report the image "z" value of the nearest pixel given x and y """ # coding: utf-8 import time import string import os import math import pylab import numpy as np from numpy import genfromtxt import matplotlib import matplotlib as mpl from matplotlib.colors import LogNorm from matplotlib.mlab import bivariate_normal import matplotlib.pyplot as plt import matplotlib.cm as cm import matplotlib.animation as animation metric = genfromtxt('D:\export.csv', delimiter=',') lines=len(metric) #print len(metric) #print len(metric[4]) #print metric[4] rowdatas=metric[:,0] for index in range(len(metric[4])-1): a=metric[:,index+1] rowdatas=np.row_stack((rowdatas,a)) #print len(rowdatas) #print len(rowdatas[4]) #print rowdatas[4] # #plt.figure(figsize=(38,38), dpi=80) #plt.plot(rowdatas[4] ) #plt.xlabel('time') #plt.ylabel('value') #plt.title("USBHID data analysis") #plt.show() linenum=1 ##如果是參數是list,則默認每次取list中的一個元素,即metric[0],metric[1],... listdata=rowdatas.tolist() print listdata[4] #fig = plt.figure() #window = fig.add_subplot(111) #line, = window.plot(listdata[4] ) fig, ax = plt.subplots() line, = ax.plot(listdata[4],lw=2) ax.grid() time_template = 'Data ROW = %d' time_text = ax.text(0.05, 0.9, '', transform=ax.transAxes) #ax = plt.axes(xlim=(0, 700), ylim=(0, 255)) #line, = ax.plot([], [], lw=2) def update(data): global linenum line.set_ydata(data) # print 'this is line: %d'%linenum time_text.set_text(time_template % (linenum)) linenum=linenum+1 # nextitem = input(u'輸入任意字符繼續: ') return line, def init(): # ax.set_ylim(0, 1.1) # ax.set_xlim(0, 10) # line.set_data(xdata) plt.xlabel('time') plt.ylabel('Time') plt.title('USBHID Data analysis') return line, ani = animation.FuncAnimation(fig, update,listdata , interval=1*1000,init_func=init,repeat=False) plt.show()
總結
以上就是本文關于python處理csv數據動態顯示曲線實例代碼的全部內容,希望對大家有所幫助。感興趣的朋友可以繼續參閱本站其他相關專題,如有不足之處,歡迎留言指出。感謝朋友們對本站的支持!
免責聲明:本站發布的內容(圖片、視頻和文字)以原創、轉載和分享為主,文章觀點不代表本網站立場,如果涉及侵權請聯系站長郵箱:is@yisu.com進行舉報,并提供相關證據,一經查實,將立刻刪除涉嫌侵權內容。